東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

A Metamodel-Based Monte Carlo Simula...

Li, Minqi.

Linked to FindBook

Google Book

Amazon

博客來

A Metamodel-Based Monte Carlo Simulation Approach for Responsive Production Planning of Manufacturing Systems.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Metamodel-Based Monte Carlo Simulation Approach for Responsive Production Planning of Manufacturing Systems./
Author:	Li, Minqi.
Description:	85 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.
Contained By:	Dissertation Abstracts International76-12B(E).
Subject:	Industrial engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3718491
ISBN:	9781321983425

A Metamodel-Based Monte Carlo Simulation Approach for Responsive Production Planning of Manufacturing Systems.
Li, Minqi.

A Metamodel-Based Monte Carlo Simulation Approach for Responsive Production Planning of Manufacturing Systems. - 85 p.

Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.

Thesis (Ph.D.)--West Virginia University, 2015.

Production planning is concerned with finding a release plan of jobs into the manufacturing system so that its actual outputs over time match the customer demand with the least cost. The biggest challenge of production planning lies in the difficulty to quantify the performance of a release plan, which is the necessary basis for plan optimization. Triggered by an input plan over a time horizon, the system outputs, work in process (WIP) and job departures, are non-stationary bivariate time series that interact with customer demand (another time series), resulting in the fulfillment/non-fulfillment of demand and in the holding cost of both WIP and finished-goods inventory. The relationship between a release plan and its resulting performance metrics (typically, mean/variance of the total cost and the demand fulfill rate is far from being adequately quantified in the existing literature of production planning. In this dissertation, a metamodel-based Monte Carlo simulation (MCS) method is developed to accurately capture the dynamic and stochastic behavior of a manufacturing system, and to allow for real-time evaluation of a release plan in terms of its performance metrics. This evaluation capability is embedded in a multi-objective optimization framework to enable the quick search of good (or optimum) release plans. The developed method has been applied to a scaled-down semiconductor fabrication system to demonstrate the quality of the metamodel-based MCS evaluation and the plan optimization results.

ISBN: 9781321983425Subjects--Topical Terms:

526216
Industrial engineering.

A Metamodel-Based Monte Carlo Simulation Approach for Responsive Production Planning of Manufacturing Systems.
LDR:02444nmm a2200289 4500 001 2116270
005 20170417135106.5
008 180830s2015 ||||||||||||||||| ||eng d
020 $a 9781321983425
035 $a (MiAaPQ)AAI3718491
035 $a AAI3718491
040 $a MiAaPQ $c MiAaPQ
100 1 $a Li, Minqi. $3 1259334
245 1 2 $a A Metamodel-Based Monte Carlo Simulation Approach for Responsive Production Planning of Manufacturing Systems.
300 $a 85 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.
500 $a Adviser: Feng Yang.
502 $a Thesis (Ph.D.)--West Virginia University, 2015.
520 $a Production planning is concerned with finding a release plan of jobs into the manufacturing system so that its actual outputs over time match the customer demand with the least cost. The biggest challenge of production planning lies in the difficulty to quantify the performance of a release plan, which is the necessary basis for plan optimization. Triggered by an input plan over a time horizon, the system outputs, work in process (WIP) and job departures, are non-stationary bivariate time series that interact with customer demand (another time series), resulting in the fulfillment/non-fulfillment of demand and in the holding cost of both WIP and finished-goods inventory. The relationship between a release plan and its resulting performance metrics (typically, mean/variance of the total cost and the demand fulfill rate is far from being adequately quantified in the existing literature of production planning. In this dissertation, a metamodel-based Monte Carlo simulation (MCS) method is developed to accurately capture the dynamic and stochastic behavior of a manufacturing system, and to allow for real-time evaluation of a release plan in terms of its performance metrics. This evaluation capability is embedded in a multi-objective optimization framework to enable the quick search of good (or optimum) release plans. The developed method has been applied to a scaled-down semiconductor fabrication system to demonstrate the quality of the metamodel-based MCS evaluation and the plan optimization results.
590 $a School code: 0256.
650 4 $a Industrial engineering. $3 526216
650 4 $a Operations research. $3 547123
650 4 $a Statistics. $3 517247
690 $a 0546
690 $a 0796
690 $a 0463
710 2 $a West Virginia University. $b Statler College of Engineering and Mineral Resources. $3 2104614
773 0 $t Dissertation Abstracts International $g 76-12B(E).
790 $a 0256
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3718491